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ACUTE MYELOID LEUKEMIA

Comparison of scoring systems evaluating suitability for intensive chemotherapy in adults with acute myeloid leukemia—a Grand Ouest Against Leukemia (GOAL) study

Leukemia volume 36, pages 2408–2417 (2022)Cite this article

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Abstract

Several scoring systems have been developed to assess suitability of individual patients for intensive acute myeloid leukemia (AML) therapy. We sought to compare the performance of these scores in a cohort of 428 consecutive adults with AML who received conventional induction chemotherapy in five academic centers in France. All scoring systems identified a subset of patients with increased 28 and 56-day mortality although the prediction accuracy was overall limited with C-statistics of ranging from 0.61 to 0.71 Overall survival (OS) prediction was more limited and restricted to scoring systems that include AML-related parameters. The outcome of 104 patients (24%) considered unsuitable for intensive chemotherapy based on criteria used in recent randomized trials was similar to that of the other 324 patients (28-day mortality, odds ratio [OR] = 1.88, P = 0.2; 56-day mortality, OR = 1.71, P = 0.21; event-free survival, hazard ratio [HR] = 1.08, P = 0.6; OS, HR = 1.25, P = 0.14) with low discrimination (C-statistic: 0.57, 0.56, 0.50, and 0.52 for 28-day, 56-day mortality, EFS, and OS, respectively). Together, our findings indicate that the accuracy of currently available approaches to identify patients at increased risk of early mortality and shortened survival after intensive AML therapy is relatively limited. Caution regarding the use of available scoring systems should be warranted in clinical decision-making.

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Fig. 1: Distribution of predictive scoring systems by early (28-day and 56-day) mortality. The proportion of patients with early mortality is represented for individual patient categories, as stratified by scoring systems.
Fig. 2: Outcome of patients stratified by each scoring ssytems.
Fig. 3: Time AUC and Brier score for prediction of mortality over time for different scoring systems.

References

  1. Sánchez‐Vizcaíno F, Tamayo C, Ramos F, Láinez‐González D, Serrano‐López J, Barba R et al. Identification of seasonal variation in the diagnosis of acute myeloid leukaemia: a population‐based study. Br J Haematol. 2022;198:545–55.

  2. Juliusson G, Antunovic P, Derolf Å, Lehmann S, Möllgård L, Stockelberg D, et al. Age and acute myeloid leukemia: real world data on decision to treat and outcomes from the Swedish Acute Leukemia Registry. Blood. 2009;113:4179–87.

    Article  CAS  Google Scholar 

  3. Appelbaum FR, Gundacker H, Head DR, Slovak ML, Willman CL, Godwin JE, et al. Age and acute myeloid leukemia. Blood. 2006;107:3481–5.

    Article  CAS  Google Scholar 

  4. Etienne A, Esterni B, Charbonnier A, Mozziconacci M-J, Arnoulet C, Coso D, et al. Comorbidity is an independent predictor of complete remission in elderly patients receiving induction chemotherapy for acute myeloid leukemia. Cancer. 2007;109:1376–83.

    Article  Google Scholar 

  5. Hjort Jakobsen L, Stidsholt Roug A, Kiesbye Øvlisen A, Werenberg Marcher C, Beier Ommen H, Theilgaard‐Mönch K, et al. Temporal changes in survival among adult patients with acute myeloid leukaemia in the period 2000–16: a Danish population‐based study. Br J Haematol. 2021;193:482–7.

    Article  Google Scholar 

  6. Juliusson G, Hagberg O, Lazarevic VL, Ölander E, Antunovic P, Cammenga J, et al. Improved survival of men 50 to 75 years old with acute myeloid leukemia over a 20-year period. Blood. 2019;134:1558–61.

    Article  CAS  Google Scholar 

  7. Kaplan ZLR, van Leeuwen N, Posthuma EFM, Visser O, Huls G, van de Loosdrecht AA, et al. Improved relative survival in older patients with acute myeloid leukemia over a 30-year period in the Netherlands: a long haul is needed to change nothing into something. Leukemia. 2022;36:596–8.

    Article  Google Scholar 

  8. Dombret H, Seymour JF, Butrym A, Wierzbowska A, Selleslag D, Jang JH, et al. International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with >30% blasts. Blood. 2015;126:291–9.

    Article  CAS  Google Scholar 

  9. Wei AH, Montesinos P, Ivanov V, DiNardo CD, Novak J, Laribi K, et al. Venetoclax plus LDAC for newly diagnosed AML ineligible for intensive chemotherapy: a phase 3 randomized placebo-controlled trial. Blood. 2020;135:2137–45.

    Article  CAS  Google Scholar 

  10. DiNardo CD, Jonas BA, Pullarkat V, Thirman MJ, Garcia JS, Wei AH, et al. Azacitidine and venetoclax in previously untreated acute myeloid leukemia. N Engl J Med. 2020;383:617–29.

    Article  CAS  Google Scholar 

  11. Sorror ML, Storer BE, Fathi AT, Brunner A, Gerds AT, Sekeres MA, et al. Multisite 11-year experience of less-intensive vs intensive therapies in acute myeloid leukemia. Blood. 2021;138:387–400.

    Article  CAS  Google Scholar 

  12. Palmieri R, Othus M, Halpern AB, Percival M-EM, Godwin CD, Becker PS, et al. Accuracy of SIE/SIES/GITMO consensus criteria for unfitness to predict early mortality after intensive chemotherapy in adults with AML or other high-grade myeloid neoplasm. JCO. 2020;38:4163–74.

    Article  CAS  Google Scholar 

  13. Walter RB, Othus M, Borthakur G, Ravandi F, Cortes JE, Pierce SA, et al. Prediction of early death after induction therapy for newly diagnosed acute myeloid leukemia with pretreatment risk scores: a novel paradigm for treatment assignment. JCO. 2011;29:4417–24.

    Article  Google Scholar 

  14. Sorror ML, Storer BE, Fathi AT, Gerds AT, Medeiros BC, Shami P, et al. Development and validation of a novel acute myeloid leukemia–composite model to estimate risks of mortality. JAMA Oncol. 2017;3:1675.

    Article  Google Scholar 

  15. Ferrara F, Barosi G, Venditti A, Angelucci E, Gobbi M, Pane F, et al. Consensus-based definition of unfitness to intensive and non-intensive chemotherapy in acute myeloid leukemia: a project of SIE, SIES and GITMO group on a new tool for therapy decision making. Leukemia. 2013;27:997–9.

    Article  CAS  Google Scholar 

  16. Sasaki K, Kadia T, Begna K, DiNardo CD, Borthakur G, Short NJ, et al. Prediction of early (4-week) mortality in acute myeloid leukemia with intensive chemotherapy. Am J Hematol. 2022;97:68–78.

    Article  CAS  Google Scholar 

  17. Pigneux A, Béné MC, Salmi L-R, Dumas P-Y, Delaunay J, Bonmati C, et al. Improved survival by adding lomustine to conventional chemotherapy for elderly patients with AML without unfavorable cytogenetics: results of the LAM-SA 2007 FILO. Trial JCO. 2018;36:3203–10.

    Article  CAS  Google Scholar 

  18. Lancet JE, Uy GL, Newell LF, Lin TL, Ritchie EK, Stuart RK, et al. CPX-351 versus 7+3 cytarabine and daunorubicin chemotherapy in older adults with newly diagnosed high-risk or secondary acute myeloid leukaemia: 5-year results of a randomised, open-label, multicentre, phase 3 trial. Lancet Haematol. 2021;8:e481–e491.

    Article  Google Scholar 

  19. Grimwade D, Hills RK, Moorman AV, Walker H, Chatters S, Goldstone AH, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood. 2010;116:354–65.

    Article  CAS  Google Scholar 

  20. Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129:424–47.

    Article  Google Scholar 

  21. Sorror ML, Maris MB, Storb R, Baron F, Sandmaier BM, Maloney DG, et al. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106:2912–9.

    Article  CAS  Google Scholar 

  22. Moons KGM, Altman DG, Reitsma JB, Ioannidis JPA, Macaskill P, Steyerberg EW, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration. Ann Intern Med. 2015;162:W1–73.

    Article  Google Scholar 

  23. Duchmann M, Micol J-B, Duployez N, Raffoux E, Thomas X, Marolleau J-P, et al. Prognostic significance of concurrent gene mutations in intensively treated patients with IDH -mutated AML: an ALFA study. Blood. 2021;137:2827–37.

    Article  CAS  Google Scholar 

  24. Fenwarth L, Thomas X, de Botton S, Duployez N, Bourhis J-H, Lesieur A, et al. A personalized approach to guide allogeneic stem cell transplantation in younger adults with acute myeloid leukemia. Blood. 2021;137:524–32.

    Article  CAS  Google Scholar 

  25. Orvain C, Othus M, Johal G, Hunault-Berger M, Appelbaum FR, Walter RB. Evolution of eligibility criteria for non-transplant randomized controlled trials in adults with acute myeloid leukemia. Leukemia. 2022:36;2002–8.

    Article  Google Scholar 

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Acknowledgements

We would like to acknowledge all the medical teams and pharmacists from each participating center for their help on identifying patients and collecting data.

Author information

Authors and Affiliations

  1. Service des maladies du sang, CHU d’Angers, Angers, France

    Christophe Desprez, Aline Schmidt-Tanguy, Mathilde Hunault-Berger & Corentin Orvain

  2. Univ Angers, CHU Angers, Inserm, CNRS, MINT, SFR ICAT, Angers, France

    Jérémie Riou

  3. Service d’hématologie clinique, CHU de Nantes, Rennes, France

    Pierre Peterlin & Patrice Chevalier

  4. Federation hospitalo-universitaire « Grand Ouest against Leukemia », Angers, France

    Pierre Peterlin, Tony Marchand, Marie-Anne Couturier, Alban Villate, Jean-Baptiste Mear, Patrice Chevalier, Gaelle Guillerm, Emmanuel Gyan, Aline Schmidt-Tanguy, Mathilde Hunault-Berger & Corentin Orvain

  5. Service d’hématologie clinique, CHU de Rennes, Rennes, France

    Tony Marchand & Jean-Baptiste Mear

  6. INSERM U1236, Université Rennes 1, Rennes, France

    Tony Marchand

  7. Service d’Hématologie Clinique, Hôpital Morvan, CHU de Brest, Rennes, France

    Marie-Anne Couturier & Gaelle Guillerm

  8. Service d’Hématologie et Thérapie Cellulaire, Hôpital Bretonneau, CHRU de Tours, CNRS EMR7001 LNOx, Université de Tours, Rennes, France

    Alban Villate & Emmanuel Gyan

  9. Université d’Angers, Inserm UMR 1307, CNRS UMR 6075, Nantes Université, CRCI2NA, F-49000, Angers, France

    Aline Schmidt-Tanguy, Mathilde Hunault-Berger & Corentin Orvain

  10. Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA

    Roland B. Walter

  11. Department of Medicine, Division of Hematology/Oncology, University of Washington, Seattle, WA, USA

    Roland B. Walter

  12. Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA

    Roland B. Walter

  13. Department of Epidemiology, University of Washington, Seattle, WA, USA

    Roland B. Walter

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  1. Christophe Desprez
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  2. Jérémie Riou
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Contributions

Conception and Design: CD, CO. Collection and Assembly of Data: CD, PP, TM, MAC, AV, JBM, PC, GG, EG. Data Analysis and Interpretation: CD, JR, ATS, RBW, MHB, CO. Manuscript Writing: All authors. Final Approval of the Manuscript: All authors.

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Correspondence to Corentin Orvain.

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Competing interests

Employment or Leadership Position: none; Consultant or Advisory Role: MHB, Erytech©; Stock Ownership: none; MHB, Abbvie, Incyte, and Jazz Pharmaceuticals, CO, Novartis; Research Funding: none; Expert Testimony: none; Patents: none; Other Remuneration: none.

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Desprez, C., Riou, J., Peterlin, P. et al. Comparison of scoring systems evaluating suitability for intensive chemotherapy in adults with acute myeloid leukemia—a Grand Ouest Against Leukemia (GOAL) study. Leukemia 36, 2408–2417 (2022). https://doi.org/10.1038/s41375-022-01677-z

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